Every year, large amounts of resources are invested by federal institutions in preventing premature deaths during adulthood worldwide. Unfortunately, the mortality impact of such interventions in a large number of target countries remains unclear because very few developing countries have complete vital registration systems to monitor adult mortality accurately. Instead, adult mortality rates are commonly estimated from retrospective data collected during household-based surveys, by asking respondents about the survival of their maternal siblings. These siblings' survival histories (SSH) are inexpensive to collect but are potentially affected by large biases, including sample selection, recall and interviewer behavior biases. As a result, estimates of the level of adult mortality in developing countries are frequently contested. Sophisticated statistical adjustment techniques have been proposed to correct for sample selection biases, but respondent errors (i.e., forgetting of siblings) affecting retrospective mortality data are considered inevitable. In this project, we will test whether a new survey instrument helps improve the quality of data on siblings' survival collected during surveys. This instrument - the siblings enhanced life calendar (SELC) - is based on recall cues and life calendars. These are simple tools that have been widely and successfully used in other areas of survey research. They have however never been used to improve the recall of adult mortality data in developing countries. We will conduct a randomized controlled trial of the new SELC, which will determine whether this new instrument improves mortality data relative to standard instruments currently in use. We will evaluate this improvement by comparing reports of mortality in each arm to a gold standard obtained from demographic surveillance. We expect that close to 400 respondents in three rural populations of Senegal will participate in this trial. If successful, the proposed SELC will constitute a new approach to eliciting retrospective mortality data that can be tested on a larger scale and possibly incorporated in national surveys of adult mortality (e.g., DHS).